NISC currently operates the following suite of production sequencing machines: 1 PacBio RS II, 4 HiSeq2500s, 1 HiSeq4000, and 3 MiSeqs. Using these platforms, we have generated over 740 billion reads in the past year. Though we remain consistently at a level of a mid-scale genome sequencing center, we have maintained advantageous economies of scale while remaining relatively agile. The adoption of many new sequencing protocols in production created the commensurate need for dramatic changes to sample tracking, flow control and primary analysis pipelines, as well as project management and cost accounting. Rapid design, development and implementation of new Laboratory Information Management System (LIMS) by a dedicated NISC team has met the initial challenges and continues to evolve quickly to adapt to a continuous flow of changes in sequencing technologies. A combination of talented IT staff and bioinformaticians have met the challenges of extremely large and complex data sets by implementing and continuously adapting pipeline programs to support rapidly evolving software associated with each of the sequencing platforms. Beyond primary analysis that results in DNA basecalls and quality scores, NISC has worked closely with members of other NHGRI research groups to implement and support high-throughput production of biologically relevant secondary analysis. One shining example of these efforts is the production scale processing of Whole Exome Sequencing (WES) data to all of our clients, the end product of which is distilled sets of variants of interest that are accessible in user-friendly fashion by the use of the in-house developed VarSifter program. The success of these programs has led to an increasing number of projects from a growing number of investigators. In 2014 we added a CLIA compliant pipeline for WES of samples originating from the NIH Clinical Center through the Clinical Center Genomics Opportunity program (https://www.genome.gov/27558725) and have completed sequencing of 1205 samples. Since the conclusion of the CCGO project, additional projects requesting the CLIA exome test has led to the processing of another 109 samples for three different groups at NIH. Publications for fiscal-year 2017 span a wide range of projects, and are summarized as follows: 1) Custom capture (n=2) (Chandrasekharappa, Chinn et al. 2017, Falik Zaccai, Savitzki et al. 2017) 2) WES projects (n = 16)(O'Brien, Lozier et al. 2016, Zhou, Yu et al. 2016, Anikster, Haack et al. 2017, Berger, Ciccone et al. 2017, Bryan, Tolman et al. 2017, Dewan, Pemov et al. 2017, Kambouris, Thevenon et al. 2017, Kwon, Connelly et al. 2017, Le Gallo, Rudd et al. 2017, Pemov, Li et al. 2017, Poretti, Snow et al. 2017, Shahrour, Staretz-Chacham et al. 2017, Stephen, Vilboux et al. 2017, Summers, Snow et al. 2017, Vilboux, Doherty et al. 2017, Vilboux, Malicdan et al. 2017) 3) Whole Genome Sequencing, Assembly and/or Annotation (n = 1) (Torok, Schiffer et al. 2016) 4) RNAseq (n = 2)(Varshney, Scott et al. 2017, Winter, Gildea et al. 2017) 5) ChIPseq, FAIREseq and ATACseq (n = 3) (Gopinath, Law et al. 2016, Loftus, Baxter et al. 2017, Roman, Cannon et al. 2017) 6) Microbiome studies (n = 3) (Conlan, Lau et al. 2016, Byrd, Deming et al. 2017, Chen, Conlan et al. 2017) 7) Pacific Biosciences amplicon sequencing (n = 1) (Hartley, Mullikin et al. 2016) 8) HIV and antibody studies (n=1) (Sheng, Schramm et al. 2017). In the foreseeable future, NISC is well positioned to provide next-gen sequence data for a multitude of investigators across NIH. We also expect increasing access to sequencing by the NIH Clinical Center with our CLIA exome test, and continuing our sequencing support for Intramural NHGRI investigators for their most promising projects. Our focus is to increase operational efficiencies of the next-gen pipeline, refine existing protocols, implement additional protocols as new sample/experimental types are requested from researchers and continue to expand the value-added data analysis packages available. Furthermore, we will continue to monitor developments in the rapidly evolving sequencing and informatics technologies, implementing those we deem most appropriate for our collaborating investigators.